I. Field of the Invention.
The present invention relates generally to the field of magnetic resonance imaging (MRI) and more particularly to systems and methods for producing multi-dimensional tissue characterization images.
II. Description of the Related Art
MRIs are used for a variety of reasons such as medical diagnosis, surgical planning, and enhanced visualization of anatomic, physiologic and pathologic features. Radio frequency signals from three dimensional tissue voxels are absorbed and then radiated when the tissue is placed in a strong magnetic field. These signals provide data for the spatial location and contrast discrimination of specific tissues, which are ultimately displayed as pixels comprising a two-dimensional MR image. These characteristics include longitudinal relaxation rate (T1), transverse relaxation rate (T2), proton density, magnetic susceptibility, and flow velocity and direction, and other biophysical properties. To emphasize contrast patterns of specific tissues of specific tissues, different image acquisition parameters or pulse sequences are utilized to produce various types of “weighed” images. The selection of different pulse sequences allows for the generation of spin echo images that are T1-weighted, T2-weighted or proton density weighted for example. Furthermore, echo planar, inversion recovery, fast spin echo and gradient echo pulse sequences or “fast scans” can be utilized to obtain images that possess additional unique tissue-contrast patterns. In each type of image, individual tissues appear differently based on their own inherent biophysical characteristics. Contrast agents sued in MRI, such as gadolinium also provide contrast for visualization of certain pathologies.
Various gray tone and color display methods have been developed for tissue characterization. Typically, gray tone methods have many limitations in the characterization since the human eye can typically only differentiate among 16 different gray tones. In a typical MRI several of the echo images are taken and compared. For example, a MRI technician may use three scans (pulse sequences) for one region of interest, such as T1-weighted, T2-weighted and inversion recovery scans. Subsequently, the doctor, or other person analyzing the scans, must look at each of the scans (which can be potentially hundreds of scans) of the particular region of interest to determine the biophysical characteristic or pathology of concern. Accordingly, there can be subjective interpretations. In colorizing attempts, many of the present colorization of MRI and CT scans simply apply colors arbitrarily without protocol and without capitalizing on the multi-parameter features of MRI.
There have been many attempts to create a single composite image from the plurality of scans as mentioned above. One such attempt is disclosed in U.S. Pat. Nos. 5,332,968 and 5,410,250, both to Brown. In these patents, single color coded composite images are formed by acquiring the plurality of gray tone images and plotting a histogram of the average pixel intensities for selected regions of interest. Based on the histogram, color masks of red, green and blue coefficients are assigned to the images of each pulse sequence such that a final combination of colors produce a series of semi-natural appearing composite image that provides automatic segmentation by color mapping that discloses specific physiological features and pathologies not easily visually identifiable in the plurality of gray tone images.
However, even with successful production of a series of single composite images, there is typically still a problem of obtaining a segmented or characterized three dimensional rendering of the region of interest. As mentioned above, a three dimensional tissue voxel is ultimately scanned into a two dimensional MRI image. In order to obtain a better three dimensional understanding of the region of interest, MRI scans typically consist of acquiring several pulse sequences of a plurality of slices through the region of interest. Even having several scans of several slices, there lacks a method of automatic tissue segmentation that is required for an accurate and immediate three dimensional rendering of regions of interest.